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Visually impaired people face lot of inconvenience to
move in and out without any proper assistance or help from
others. Hence it becomes mandate to provide an user-friendly
device to assist them. Thus, a solution for such people is proposed
by an efficient technique like machine learning algorithm. In
order to access machine learning technique. The necessary data
input are obtained using a technique called Image acquisition.
Multiple technologies like Convolutional Neural Network(CNN)
is implemented. Convolutional Neural Network(CNN) is an
algorithm used for image processing. It is a class of artificial
neural networks that has been successfully applied to analyze the
visual image. Using image processing we can recognize object and
identify gender. The object in the vicinity are captured as images
using camera. It can detect every object and identify gender
precisely with in some prior distance. The captured images are
then converted into audio signals for providing convenient means
for assisting blind people. Thus, a flexible guiding mechanism
with user friendliness is developed for helping blind people.
Keywords:
OBJECT, Keras, OpenCV, GENDER, Tensorflow, GTTS.
Cite Article:
"Blind Assistance Using Machine Learning ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 7, page no.1399 - 1403, July-2022, Available :http://www.ijrti.org/papers/IJRTI2207219.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator